Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network

doi:10.1155/2020/5795976

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能制造技术与系统研究中心

	Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network
	Yuan, Jian-ye 2; Nan, Xin-yuan 2; Li, Cheng-rong 3; Sun, Le-le 1
刊名	MATHEMATICAL PROBLEMS IN ENGINEERING
	2020-11-30
卷号	2020 页码:6
ISSN号	1024-123X
DOI	10.1155/2020/5795976
通讯作者	Nan, Xin-yuan(yuanxianshengo@163.com)
英文摘要	Considering that the garbage classification is urgent, a 23-layer convolutional neural network (CNN) model is designed in this paper, with the emphasis on the real-time garbage classification, to solve the low accuracy of garbage classification and recycling and difficulty in manual recycling. Firstly, the depthwise separable convolution was used to reduce the Params of the model. Then, the attention mechanism was used to improve the accuracy of the garbage classification model. Finally, the model fine-tuning method was used to further improve the performance of the garbage classification model. Besides, we compared the model with classic image classification models including AlexNet, VGG16, and ResNet18 and lightweight classification models including MobileNetV2 and SuffleNetV2 and found that the model GAF_dense has a higher accuracy rate, fewer Params, and FLOPs. To further check the performance of the model, we tested the CIFAR-10 data set and found the accuracy rates of the model (GAF_dense) are 0.018 and 0.03 higher than ResNet18 and SufflenetV2, respectively. In the ImageNet data set, the accuracy rates of the model (GAF_dense) are 0.225 and 0.146 higher than Resnet18 and SufflenetV2, respectively. Therefore, the garbage classification model proposed in this paper is suitable for garbage classification and other classification tasks to protect the ecological environment, which can be applied to classification tasks such as environmental science, children's education, and environmental protection.
WOS研究方向	Engineering ; Mathematics
语种	英语
出版者	HINDAWI LTD
WOS记录号	WOS:000599836000005
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42776]
专题	自动化研究所_智能制造技术与系统研究中心
通讯作者	Nan, Xin-yuan
作者单位	1.Shandong Huayu Univ Technol, Sch Elect Engn, Dezhou 253034, Peoples R China 2.Xinjiang Univ, Sch Elect Engn, Urumqi 830047, Peoples R China 3.Chinese Acad Sci, Inst Automat, Intelligent Mfg Technol & Syst Res Ctr, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Yuan, Jian-ye,Nan, Xin-yuan,Li, Cheng-rong,et al. Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020:6.
APA	Yuan, Jian-ye,Nan, Xin-yuan,Li, Cheng-rong,&Sun, Le-le.(2020).Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network.MATHEMATICAL PROBLEMS IN ENGINEERING,2020,6.
MLA	Yuan, Jian-ye,et al."Research on Real-Time Multiple Single Garbage Classification Based on Convolutional Neural Network".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020):6.